參考文獻: | Bacchiocchi, E., Bastianin, A., Missale, A., and Rossi, E. (2016). Structural Analysis with Mixed Frequencies: Monetary Policy, Uncertainty and Gross Capital Flows. JRC Working Papers in Economics and Finance, 2016/4.
Beirne, J., Renzhi, N., and Volz, U. (2023). When the United States and the People's Republic of China Sneeze: Monetary Policy Spillovers to Asian Economies. Open Economies Review, 34, 519–540.
Bluwstein, K., and Canova, F. (2016). Beggar-Thy-Neighbor? The International Effects of ECB Unconventional Monetary Policy Measures. International Journal of Central Banking, 12(3), 69–120.
Bonser-Neal, C., and Roley, V.V., and Sellon, G.H., Jr. (1998). Monetary Policy Actions, Intervention, and Exchange Rates: A Reexamination of the Empirical Relationships Using Federal Funds Rate Target Data. The Journal of Business, 71(2), 147–177.
Breitenlechner, M., Georgiadis, G., and Schumann, B. (2022). What Goes Around Comes Around: How Large are Spillbacks from US Monetary Policy? Journal of Monetary Economics, 131, 45–60.
Durdu, C.B., and Martin, A., and Zer, I. (2019). The Role of U.S. Monetary Policy in Global Banking Crises. Finance and Economics Discussion Series, 2019(39).
Bu, C., and Rogers, J., and Wu, W. (2021). A unified measure of Fed monetary policy shocks. Journal of Monetary Economics, 118, 331–349.
Federal Reserve Bank of Philadelphia (2025/1/30). Compilation, Tealbook (formerly Greenbook) Data Sets. Federal Reserve Bank of Philadelphia.
Feldkircher, M., Huber, F., and Pfarrhofer, M. (2021). Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession. Scottish Journal of Political Economy, 68, 287–297.
Ferrara, L., and Guérin, P. (2018). What are the Macroeconomic Effects of High-Frequency uncertainty shocks? Journal of Applied Econometrics, 33(5), 662–679.
Foroni, C., and Marcellino, M. (2014). Mixed-Frequency Structural Models:Identification, Estimation, and Policy Analysis. Journal of Applied Econometrics, 29, 1118–1144.
Francis, N., Ghysels , E., and Owyang, MT. (2011). The Low-Frequency Impact of Daily Monetary Policy Shocks. Federal Reserve Bank of St. Louis Working Paper, 2011(9).
Georgiadis, G. (2016). Determinants of Global Spillovers from US Monetary Policy. Journal of International Money and Finance, 67, 41–61.
Ghysels, E., Santa-Clara, P., and Valkanov, R. (2004). The MIDAS Touch: Mixed Data Sampling Regression Models. CIRANO Working Papers, 2004(20).
Ghysels, E., Sinko, A., and Valkanov, R. (2007). MIDAS Regressions: Further Results and New Directions. Econometric Reviews, 26(1), 53–90.
Ghysels, E., Kvedaras, V., and Zemlys, V. (2016). Mixed Frequency Data Sampling Regression Models: The R Package midasr. Journal of Statistical Software, 72(4), 1–35.
Ghysels, E., Kvedaras, V., and Zemlys, V. (2020). Mixed Data Sampling (MIDAS) Regression Models. Handbook of Statistics, 42, 117–153.
Jarociński, M., and Karadi, P. (2020). Deconstructing Monetary Policy Surprises—The Role of Information Shocks. American Economic Journal: Macroeconomics, 12(2), 1–43.
Jordà, Ò. (2023). Local Projections for Applied Economics. Federal Reserve Bank of San Francisco Working Paper, 2023(16).
Lastauskas, P., and Nguyen, A.D.M. (2023). Global Impacts of US Monetary Policy Uncertainty Shocks. Journal of International Economics, 145.
Lin (2025). Real Time Data and Policy Evaluation. Working Paper.
Marcellino, M., and Sivec, V. (2016). Monetary, Fiscal and Oil Shocks: Evidence based on Mixed Frequency Structural FAVARs. Journal of Econometrics, 193, 335–348.
McCracken, M.W., Owyang , M., and Sekhposyan, T. (2015). Real-Time Forecasting with a Large, Mixed Frequency, Bayesian VAR. Federal Reserve Bank of St. Louis Working Paper, 2015(30).
Mohaddes, K., and Raissi, M. (2020). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2019Q4 University of Cambridge: Judge Business School (mimeo).
Mohaddes, K., and Raissi, M. (2024). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3. University of Cambridge: Judge Business School (mimeo).
Romer, C.D., and Romer, D.H. (2004). A New Measure of Monetary Shocks: Derivation and Implications. American Economic Review, 94(4), 1055–1084.
Rooj, D., and Sengupta, R. (2018). Monetary Policy and Private Investment in India: The MIDAS Experience. Advances in Finance & Applied Economics, 119–131.
Schumacher, C. (2016). A Comparison of MIDAS and Bridge Equations. International Journal of Forecasting, 32(2), 257–270.
Ugazio, G., and Xin, W. (2024). U.S. Monetary Policy Spillovers to Middle East and Central Asia: Shocks, Fundamentals, and Propagations. IMF Working Paper, 2024(014).
Wang, D., Liu, Q., and Li, S. (2024). Analysing the Evolving Effectiveness of Monetary Policy Instruments in China: Insights from the TVPSV-MF-BFAVAR Framework. Applied Economics.
Wieland, J. (2021). Compilation, Updated Romer-Romer Monetary Policy Shocks. Ann Arbor, MI: Inter-university Consortium for Political and Social Research. |